TrustChain-IoT: A QoS-Aware Secure Blockchain Model

Abstract

Blockchain technology offers strong security for distributed systems; however, its integration with large-scale Internet of Things (IoT) networks is limited by QoS instability, high computational overhead, and vulnerability of miner nodes to targeted attacks. This paper proposes a trust-based, QoS-aware blockchain framework for secure IoT environments. The model employs a dynamic trust evaluation mechanism to select miner nodes based on temporal security and QoS performance, ensuring reliable and efficient consensus. Additionally, location-aware clustering enables stochastic miner selection, improving resilience against internal and external threats. To enhance scalability, an Elephant Herding Optimization (EHO)-based sidechaining approach is introduced, which adaptively partitions and merges the blockchain using parameters such as chain length, mining delay, and energy consumption. This enables efficient and low-complexity mining for large-scale deployments. The proposed system is evaluated under DDoS, Finney, and Sybil attacks, demonstrating robust and consistent performance. Experimental results show a 15.3% reduction in computational delay, 9.4% lower energy consumption, 3.2% improvement in packet delivery ratio, and 5.9% higher throughput compared to existing methods. These results validate the effectiveness of the proposed framework for secure and scalable IoT applications.

Introduction

Designing a blockchain-based IoT security network is a complex multi-domain task requiring decisions on encryption, block structure, miner selection, and consensus models, while optimizing energy use, speed, and attack mitigation. A typical system routes content securely to IoT clients using access tokens verified by blockchain authorities, with mining delays increasing as the chain grows.

Key approaches from the literature include:

1. Sidechain-based trust models – Splitting the blockchain into multiple sidechains managed under a central hub, using PBFT consensus and smart contracts to enhance QoS and mitigate attacks like DDoS and wormholes.
2. Dual-fog architectures – Dividing responsibilities between Fog-Cloud and Fog-Mining layers, classifying requests as real-time, non-real-time, or delay-tolerant, improving latency, throughput, and energy efficiency.
3. Dynamic consensus protocols – Using permissioned blockchains and machine learning (Deep Q-Learning) to adapt consensus mechanisms based on application QoS and security requirements, balancing speed, energy use, and security.
4. Trust-aware congestion control (BCOOL) – Mitigating transaction overload in high-traffic IoT networks to maintain throughput and QoS.

Overall, these models aim to combine security, trust, and QoS awareness, though challenges remain in scalability, hardware costs, and system complexity, suggesting future work in machine learning–driven optimization for adaptive, cost-efficient blockchain-IoT networks.

Conclusion

This paper presented HSBPQ, a trust-aware blockchain-based IoT framework integrating intelligent miner selection with an Elephant Herding Optimization (EHO)-driven sidechaining mechanism. The proposed model enhances security, scalability, and QoS in large-scale IoT deployments by enabling reliable miner selection and efficient blockchain partitioning. It demonstrates strong resilience against DDoS, Sybil, and Finney attacks while reducing computational delay and energy consumption, and improving throughput. Comparative results confirm that HSBPQ outperforms existing approaches such as TBRA, QSPB, and PoET. These outcomes validate its suitability for secure and efficient real-world IoT network applications.

References

[1] S. Ahmad, H. Farman, M. Aslam, F. Zaman and A. Jan, \"Blockchain-empowered distributed data management for secure and scalable IoT networks,\"IEEE Internet of Things Journal, vol. 11, no. 3, pp. 2575–2587, Feb. 2024, doi: 10.1109/JIOT.2023.3330482. [2] Y. Zhao, L. Qi, W. Dou, J. Yu and Y. Xu, \"A Blockchain-Based Cross-Domain Authentication Architecture for Internet of Things,\"IEEE Transactions on Network and Service Management, vol. 20, no. 1, pp. 123–137, Mar. 2023, doi: 10.1109/TNSM.2022.3216451. [3] A. Y. Alzahrani, M. Hammoudeh and S. A. Alqahtani, \"Towards a Trust-Aware Blockchain Architecture for IoT: A Deep Reinforcement Learning Approach,\"IEEE Internet of Things Journal, vol. 9, no. 12, pp. 8950–8963, Jun. 2022, doi: 10.1109/JIOT.2021.3116437. [4] K. Dai, L. Wang, H. Wang, and Y. Qin, \"BCOOL: Blockchain Congestion Control for IoT Systems,\"IEEE Transactions on Industrial Informatics, vol. 17, no. 12, pp. 8884–8892, Dec. 2021, doi: 10.1109/TII.2021.3073727. [5] J. Ren, G. Yu, Y. He, and Y. Li, \"Latency Optimization for Resource Allocation in Blockchain-Enabled IoT Networks,\"IEEE Transactions on Wireless Communications, vol. 20, no. 4, pp. 2650–2664, Apr. 2021, doi: 10.1109/TWC.2021.3052058. [6] S. Rathore and J. H. Park, \"Blockchain-Based Security for Cyber-Physical Systems: State-of-the-Art and Future Challenges,\"IEEE Consumer Electronics Magazine, vol. 10, no. 2, pp. 84–90, Mar. 2021, doi: 10.1109/MCE.2020.3024344. [7] C. Qiu, H. Yao, F. R. Yu, C. Jiang and S. Guo, \"A Service-Oriented Permissioned Blockchain for the Internet of Things,\"IEEE Transactions on Services Computing, vol. 13, no. 2, pp. 203–215, Mar.–Apr. 2020, doi: 10.1109/TSC.2019.2948870. [8] R. Lu, X. Li, X. Liang and X. Shen, \"EPPDR: An Efficient Privacy-Preserving Data Reporting Scheme for Smart Grid Communications,\"IEEE Transactions on Smart Grid, vol. 5, no. 1, pp. 760–770, Jan. 2019, doi: 10.1109/TSG.2013.2279585. [9] L. Xu, L. Chen and Z. Gao, \"Smart Contract Based Lightweight Authentication Scheme for Wireless Body Area Network,\"IEEE Access, vol. 6, pp. 51293–51301, 2018, doi: 10.1109/ACCESS.2018.2867545. [10] S. Nakamoto, \"Bitcoin: A Peer-to-Peer Electronic Cash System,\" White Paper, 2008. [Online]. Available: https://bitcoin.org/bitcoin.pdf. [11] W. Viriyasitavat, L. D. Xu, Z. Bi, D. Hoonsopon and N. Charoenruk, \"Managing QoS of Internet-of-Things Services Using Blockchain,\" in IEEE Transactions on Computational Social Systems, vol. 6, no. 6, pp. 1357-1368, Dec. 2019, doi: 10.1109/TCSS.2019.2919667. [12] R. A. Memon, J. P. Li, M. I. Nazeer, A. N. Khan and J. Ahmed, \"DualFog-IoT: Additional Fog Layer for Solving Blockchain Integration Problem in Internet of Things,\" in IEEE Access, vol. 7, pp. 169073-169093, 2019, doi: 10.1109/ACCESS.2019.2952472. [13] C. Qiu, H. Yao, F. R. Yu, C. Jiang and S. Guo, \"A Service-Oriented Permissioned Blockchain for the Internet of Things,\" in IEEE Transactions on Services Computing, vol. 13, no. 2, pp. 203-215, 1 March-April 2020, doi: 10.1109/TSC.2019.2948870. [14] C. Qiu, X. Ren, Y. Cao and T. Mai, \"Deep Reinforcement Learning Empowered Adaptivity for Future Blockchain Networks,\" in IEEE Open Journal of the Computer Society, vol. 2, pp. 99-105, 2021, doi: 10.1109/OJCS.2020.3010987. [15] M. Debe, K. Salah, M. H. Ur Rehman and D. Svetinovic, \"Monetization of Services Provided by Public Fog Nodes Using Blockchain and Smart Contracts,\" in IEEE Access, vol. 8, pp. 20118-20128, 2020, doi: 10.1109/ACCESS.2020.2968573. [16] Z. Liu, L. Gao, Y. Liu, X. Guan, K. Ma and Y. Wang, \"Efficient QoS Support for Robust Resource Allocation in Blockchain-Based Femtocell Networks,\" in IEEE Transactions on Industrial Informatics, vol. 16, no. 11, pp. 7070-7080, Nov. 2020, doi: 10.1109/TII.2019.2939146. [17] S. Rathore, J. H. Park and H. Chang, \"Deep Learning and Blockchain-Empowered Security Framework for Intelligent 5G-Enabled IoT,\" in IEEE Access, vol. 9, pp. 90075-90083, 2021, doi: 10.1109/ACCESS.2021.3077069. [18] S. Maaroufi and S. Pierre, \"BCOOL: A Novel Blockchain Congestion Control Architecture Using Dynamic Service Function Chaining and Machine Learning for Next Generation Vehicular Networks,\" in IEEE Access, vol. 9, pp. 53096-53122, 2021, doi: 10.1109/ACCESS.2021.3070023. [19] W. Viriyasitavat, L. D. Xu and Z. Bi, \"Specification Patterns of Service-Based Applications Using Blockchain Technology,\" in IEEE Transactions on Computational Social Systems, vol. 7, no. 4, pp. 886-896, Aug. 2020, doi: 10.1109/TCSS.2020.2999574. [20] F. Guo, F. R. Yu, H. Zhang, H. Ji, M. Liu and V. C. M. Leung, \"Adaptive Resource Allocation in Future Wireless Networks With Blockchain and Mobile Edge Computing,\" in IEEE Transactions on Wireless Communications, vol. 19, no. 3, pp. 1689-1703, March 2020, doi: 10.1109/TWC.2019.2956519. [21] M. Liu, Y. Teng, F. R. Yu, V. C. M. Leung and M. Song, \"A Deep Reinforcement Learning-Based Transcoder Selection Framework for Blockchain-Enabled Wireless D2D Transcoding,\" in IEEE Transactions on Communications, vol. 68, no. 6, pp. 3426-3439, June 2020, doi: 10.1109/TCOMM.2020.2974738. [22] J. Liu, S. Guo, Y. Shi, L. Feng and C. Wang, \"Decentralized Caching Framework Toward Edge Network Based on Blockchain,\" in IEEE Internet of Things Journal, vol. 7, no. 9, pp. 9158-9174, Sept. 2020, doi: 10.1109/JIOT.2020.3003700. [23] A. A. Abdellatif, A. Z. Al-Marridi, A. Mohamed, A. Erbad, C. F. Chiasserini and A. Refaey, \"ssHealth: Toward Secure, Blockchain-Enabled Healthcare Systems,\" in IEEE Network, vol. 34, no. 4, pp. 312-319, July/August 2020, doi: 10.1109/MNET.011.1900553. [24] V. K. Rathi et al., \"A Blockchain-Enabled Multi Domain Edge Computing Orchestrator,\" in IEEE Internet of Things Magazine, vol. 3, no. 2, pp. 30-36, June 2020, doi: 10.1109/IOTM.0001.1900089. [25] X. Lin, J. Wu, A. K. Bashir, J. Li, W. Yang and J. Piran, \"Blockchain-Based Incentive Energy-Knowledge Trading in IoT: Joint Power Transfer and AI Design,\" in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2020.3024246. [26] A. Kumari, S. Tanwar, S. Tyagi and N. Kumar, \"Blockchain-Based Massive Data Dissemination Handling in IIoT Environment,\" in IEEE Network, vol. 35, no. 1, pp. 318-325, January/February 2021, doi: 10.1109/MNET.011.2000355. [27] H. ElHusseini, C. Assi, B. Moussa, R. Attallah and A. Ghrayeb, \"Blockchain, AI and Smart Grids: The Three Musketeers to a Decentralized EV Charging Infrastructure,\" in IEEE Internet of Things Magazine, vol. 3, no. 2, pp. 24-29, June 2020, doi: 10.1109/IOTM.0001.1900081. [28] M. Karakus and E. Guler, \"RoutingChain: A Proof-of-Concept Model for a Blockchain-Enabled QoS-Based Inter-AS Routing in SDN,\" 2020 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), 2020, pp. 1-6, doi: 10.1109/BlackSeaCom48709.2020.9235021. [29] H. Lee, K. Sung, K. Lee, J. Lee and S. Min, \"Economic Analysis of Blockchain Technology on Digital Platform Market,\" 2018 IEEE 23rd Pacific Rim International Symposium on Dependable Computing (PRDC), 2018, pp. 94-103, doi: 10.1109/PRDC.2018.00020. [30] J. Zheng, X. Dong, Q. Liu, X. Zhu and W. Tong, \"Blockchain-based secure digital asset exchange scheme with QoS-aware incentive mechanism,\" 2019 IEEE 20th International Conference on High Performance Switching and Routing (HPSR), 2019, pp. 1-6, doi: 10.1109/HPSR.2019.8808111. [31] D. B. Rawat and A. Alshaikhi, \"Leveraging Distributed Blockchain-based Scheme for Wireless Network Virtualization with Security and QoS Constraints,\" 2018 International Conference on Computing, Networking and Communications (ICNC), 2018, pp. 332-336, doi: 10.1109/ICCNC.2018.8390344. [32] M. Liu, F. R. Yu, Y. Teng, V. C. M. Leung and M. Song, \"Deep Reinforcement Learning (DRL)-Based Transcoder Selection for Blockchain-Enabled Video Streaming,\" 2018 IEEE Globecom Workshops (GC Wkshps), 2018, pp. 1-6, doi: 10.1109/GLOCOMW.2018.8644290. [33] Sodhro, A.H., Pirbhulal, S., Muzammal, M. et al. Towards Blockchain-Enabled Security Technique for Industrial Internet of Things Based Decentralized Applications. J Grid Computing 18, 615–628 (2020). https://doi.org/10.1007/s10723-020-09527-x [34] Kochovski, P., Stankovski, V., Gec, S. et al. Smart Contracts for Service-Level Agreements in Edge-to-Cloud Computing. J Grid Computing 18, 673–690 (2020). https://doi.org/10.1007/s10723-020-09534-y [35] Asghari, P., Rahmani, A.M. & Javadi, H.H.S. Privacy-aware cloud service composition based on QoS optimization in Internet of Things. J Ambient Intell Human Comput (2020). https://doi.org/10.1007/s12652-020-01723-7 [36] Xu, X., Chen, Y., Yuan, Y. et al. Blockchain-based cloudlet management for multimedia workflow in mobile cloud computing. Multimed Tools Appl 79, 9819–9844 (2020). https://doi.org/10.1007/s11042-019-07900-x [37] Qaisar Shaheen, Muhammad Shiraz, Muhammad Usman Hashmi, Danish Mahmood, Zhu zhiyu, Rizwan Akhtar, \"A Lightweight Location-Aware Fog Framework (LAFF) for QoS in Internet of Things Paradigm,\" Mobile Information Systems, vol. 2020, Article ID 8871976, 15 pages, 2020. https://doi.org/10.1155/2020/8871976 [38] Li, W., Wu, J., Cao, J. et al. Blockchain-based trust management in cloud computing systems: a taxonomy, review and future directions. J Cloud Comp 10, 35 (2021). https://doi.org/10.1186/s13677-021-00247-5 [39] A. S. M. S. Hosen et al., \"Blockchain-Based Transaction Validation Protocol for a Secure Distributed IoT Network,\" in IEEE Access, vol. 8, pp. 117266-117277, 2020, doi: 10.1109/ACCESS.2020.3004486. [40] Zhang, Jianting & Hong, Zicong & Qiu, Xiaoyu & Zhan, Yufeng & Guo, Song & Chen, Wuhui. (2020). SkyChain: A Deep Reinforcement Learning-Empowered Dynamic Blockchain Sharding System. 1-11. 10.1145/3404397.3404460. [41] Li, D, Deng, L, Cai, Z, Souri, A. Blockchain as a service models in the Internet of Things management: Systematic review. Trans Emerging Tel Tech. 2020; e4139. https://doi.org/10.1002/ett.4139 [42] PF-BTS: A Privacy-Aware Fog-enhanced Blockchain-assisted task scheduling, https://www.sciencedirect.com/science/article/pii/S0306457320308888 [43] J. Yun, Y. Goh and J. -M. Chung, \"Trust-Based Shard Distribution Scheme for Fault-Tolerant Shard Blockchain Networks,\" in IEEE Access, vol. 7, pp. 135164-135175, 2019, doi: 10.1109/ACCESS.2019.2942003. [44] C. Huang et al., \"RepChain: A Reputation-Based Secure, Fast, and High Incentive Blockchain System via Sharding,\" in IEEE Internet of Things Journal, vol. 8, no. 6, pp. 4291-4304, 15 March15, 2021, doi: 10.1109/JIOT.2020.3028449. [45] S. Kim, \"Two-Phase Cooperative Bargaining Game Approach for Shard-Based Blockchain Consensus Scheme,\" in IEEE Access, vol. 7, pp. 127772-127780, 2019, doi: 10.1109/ACCESS.2019.2939778. [46] A. Hafid, A. S. Hafid and M. Samih, \"New Mathematical Model to Analyze Security of Sharding-Based Blockchain Protocols,\" in IEEE Access, vol. 7, pp. 185447-185457, 2019, doi: 10.1109/ACCESS.2019.2961065. [47] A. Hafid, A. S. Hafid and M. Samih, \"A Novel Methodology-Based Joint Hypergeometric Distribution to Analyze the Security of Sharded Blockchains,\" in IEEE Access, vol. 8, pp. 179389-179399, 2020, doi: 10.1109/ACCESS.2020.3027952. [48] A. Asheralieva and D. Niyato, \"Reputation-Based Coalition Formation for Secure Self-Organized and Scalable Sharding in IoT Blockchains With Mobile-Edge Computing,\" in IEEE Internet of Things Journal, vol. 7, no. 12, pp. 11830-11850, Dec. 2020, doi: 10.1109/JIOT.2020.3002969. [49] J. Yun, Y. Goh and J. -M. Chung, \"DQN-Based Optimization Framework for Secure Sharded Blockchain Systems,\" in IEEE Internet of Things Journal, vol. 8, no. 2, pp. 708-722, 15 Jan.15, 2021, doi: 10.1109/JIOT.2020.3006896. [50] M. H. Manshaei, M. Jadliwala, A. Maiti and M. Fooladgar, \"A Game-Theoretic Analysis of Shard-Based Permissionless Blockchains,\" in IEEE Access, vol. 6, pp. 78100-78112, 2018, doi: 10.1109/ACCESS.2018.2884764. [51] A. Hafid, A. S. Hafid and M. Samih, \"Scaling Blockchains: A Comprehensive Survey,\" in IEEE Access, vol. 8, pp. 125244-125262, 2020, doi: 10.1109/ACCESS.2020.3007251. [52] D. Jia, J. Xin, Z. Wang and G. Wang, \"Optimized Data Storage Method for Sharding-Based Blockchain,\" in IEEE Access, vol. 9, pp. 67890-67900, 2021, doi: 10.1109/ACCESS.2021.3077650. [53] N. Sohrabi and Z. Tari, \"ZyConChain: A Scalable Blockchain for General Applications,\" in IEEE Access, vol. 8, pp. 158893-158910, 2020, doi: 10.1109/ACCESS.2020.3020319. [54] A. Mizrahi and O. Rottenstreich, \"State Sharding with Space-aware Representations,\" 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2020, pp. 1-9, doi: 10.1109/ICBC48266.2020.9169402.

Copyright

Copyright © 2026 Abhijit Maidamwar, Manoj Lade, Dr. Pankaj Kawadkar, Swapnali Moon. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.